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Thomas L. Black

JUNE 1994 NMC NOTES 265NMC NOTESThe New NMC Mesoscale Eta Model: Description and Forecast Examples THOMAS L. BLACKDevelopment Division, National Meteorological Center, NWS/NOAA, Washington, D.C.25 October 1993 and 1 February 1994ABSTRACT In mid-1994 a new version of the Eta Model will begin producing operational forecast guidance down tomesoscale ranges. This version

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Jaymes S. Kenyon, Daniel Keyser, Lance F. Bosart, and Michael S. Evans

1. Introduction In the most rudimentary sense, forecasts of precipitation accumulation require the consideration of both precipitation rate and duration (e.g., Doswell et al. 1996 ; Evans and Jurewicz 2009 ). Mesoscale precipitation bands, hereafter called mesoscale bands, are frequently observed in conjunction with extratropical cyclones, and enhanced precipitation rates within mesoscale bands can have an appreciable impact on precipitation accumulation. Moreover, because mesoscale bands

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Jaymes S. Kenyon, Daniel Keyser, Lance F. Bosart, and Michael S. Evans

1. Introduction In the most rudimentary sense, forecasts of precipitation accumulation require the consideration of both precipitation rate and duration (e.g., Doswell et al. 1996 ; Evans and Jurewicz 2009 ). Mesoscale precipitation bands, hereafter called mesoscale bands, are frequently observed in conjunction with extratropical cyclones, and enhanced precipitation rates within mesoscale bands can have an appreciable impact on precipitation accumulation. Moreover, because mesoscale bands

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Jeffrey D. Duda and William A. Gallus Jr.

precipitation forecasts . Wea. Forecasting , 24 , 1485 – 1497 . Bryan, G. H. , Wyngaard J. C. , and Fritsch J. M. , 2003 : Resolution requirements for the simulation of deep moist convection . Mon. Wea. Rev. , 131 , 2394 – 2416 . Davis, C. , Brown B. , and Bullock R. , 2006 : Object-based verification of precipitation forecasts. Part I: Methods and application to mesoscale rain areas . Mon. Wea. Rev. , 134 , 1772 – 1784 . Done, J. , Davis C. A. , and Weisman M. , 2004 : The

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Chanh Kieu, Cole Evans, Yi Jin, James D. Doyle, Hao Jin, and Jonathan Moskaitis

depend on the boundary conditions derived from global models. Specifically, we wish to quantify a relationship between track and intensity errors for the Coupled Ocean–Atmosphere Mesoscale Prediction System for Tropical Cyclone (COAMPS-TC) model in this study. This question is of importance not only for future model development, but also of significance for further research on extracting the intrinsic intensity variability from real-time TC forecasts in different basins as discussed in K18 . Thus

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P. Goswami and S. Mallick

may primarily arise from the projection of model data on a given horizontal and vertical grid-to-point (station) observation. This part of the bias may be expected to be somewhat systematic in nature, arising, as it does, from an adopted grid and methodology for interpolation. Recently, Steed and Mass (2004) experimented with several different spatial techniques of applying bias correction to forecasts of temperature from a mesoscale model. Eckel and Mass (2005) applied bias correction on

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Ariel E. Cohen, Steven M. Cavallo, Michael C. Coniglio, Harold E. Brooks, and Israel L. Jirak

)–(i) The 21-h forecast of simulated composite reflectivity (dB Z ) for each WRF PBL member valid at 0900 UTC 13 Feb 2007 and (j) the observed mosaic composite reflectivity from the NCAR Mesoscale and Microscale Meteorology Laboratory Image Archive ( NCAR 2017 ) at 0900 UTC 13 Feb 2007. White ovals are overlaid in the panels to indicate regions of convection referenced within the main text, relevant for differences in convective mode between simulated convection and the observations. The color scale for

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David J. Stensrud, Geoffrey S. Manikin, Eric Rogers, and Kenneth E. Mitchell

guidance to forecasters on the evolution of the parameters used to evaluate the potential for heavy precipitation and severe thunderstorms. However, as our understanding of these types of events has improved, the important roles played by mesoscale features have been highlighted ( Maddox et al. 1979 , 1980 ; Olson 1985 ; Doswell 1987 ; Funk 1991 ; Doswell et al. 1993 ). During the warm season, Heideman and Fritsch (1988) show that over 80% of the more significant precipitation events 1 are

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Steven E. Koch and Christopher O’Handley

waves can exert important controls upon convection and mesoscale precipitation patterns, but in general, the operational community mistakenly perceives gravity waves as being too inconsequential, or occurring too infrequently, or being too difficult to forecast and diagnose, to be worthy of consideration in a daily forecast environment. Issues that immediately arise in this weather forecasting context include the following: 1) What kinds of gravity waves are important to the weather? 2) How

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Eric P. Grimit and Clifford F. Mass

Pennsylvania State University–National Center for Atmospheric Research fifth-generation Mesoscale Model (PSU–NCAR MM5; Grell et al. 1994 ) suggest diminishing returns as grid spacing drops below 12 km, when evaluated using standard measures of forecast skill ( Mass et al. 2002 ). Furthermore, numerical model forecasts can be very sensitive to slight changes in the larger-scale initial conditions ( Brooks et al. 1992 ). Recognition of such predictability issues has led to increased interest in developing

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